System and method for general search parameters having quantized relevance values that are associated with a user

ABSTRACT

The system and method comprises enhancement of results for a search engine, wherein the results from the search engine are refined or reorganized, based upon information from an identified secondary source. The results obtained using a conventional search are compared against the identified secondary source, e.g. a ratings service, and are filtered and/or sorted appropriately. In some embodiments, identification of the secondary source, such as a ratings service comprising information which may supplement the subject of a search query, is based upon information entered by the user. In alternate embodiments, the secondary source is associated with a user, as part of general user-specified search parameters, wherein one or more parameters are consulted automatically for searches for appropriate subject matter.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of and claims priority to U.S.application Ser. No. 11/471,927, originally entitled Search EnhancementSystem Having Ranked General Search Parameters, filed 20 Jun. 2006,which is a Continuation of and claims priority to U.S. application Ser.No. 10/685,749, originally entitled Search Enhancement System HavingPersonal Search Parameters, filed 14 Oct. 2003, which was issued as U.S.Pat. No. 7,165,119 on 16 Jan. 2007.

U.S. application Ser. No. 11/471,927, originally entitled SearchEnhancement System Having Ranked General Search Parameters, filed 20Jun. 2006, is also a Continuation of and claims priority to U.S.application Ser. No. 10/685,747, entitled Search Enhancement System withInformation from a Selected Source, filed 14 Oct. 2003.

This Application is also a Continuation of and claims priority to U.S.application Ser. No. 10/685,747, entitled Search Enhancement System withInformation from a Selected Source, filed 14 Oct. 2003.

Each of the aforementioned documents are incorporated herein in theirentirety by this reference thereto.

FIELD OF THE INVENTION

The invention relates to the search and retrieval of information orcontent in a network environment. More particularly, the inventionrelates to the enhancement of search results, based upon informationreceived from a user and/or an external source.

BACKGROUND OF THE INVENTION

Conventional search engines compare input search terms against metadata,to identify displayable results. Some search processes also allow forrefined searching in input terms, against particular identified types ofmetadata. For example, during a search query at a search engine, a usermay be able to enter either a word string, e.g. “serial number”, or acorresponding abbreviation, e.g. “SN”, to indicate that subsequentsearch terms should be applied against serial number metadata.Furthermore, some conventional search engines permit comparison of inputsearch terms against full or partial text.

When applying conventional search technology, users typically obtainseveral pages of search results for any given search query,necessitating an extended period of review. For example, a commonproblem which is often encountered with conventional search queries isthat the found set of matching sites or information sources, ordocuments is often too large, i.e. too broad, such as if too few searchterms are entered within a search string, or if the search terms are toogeneral. A user must often either manually browse through a large numberof found sources to find relevant sites, or must perform a differentsearch, typically having different terms and/or additional terms, in thehopes of more accurately finding the desired sites and/or information.

A similar problem that is also encountered with conventional searchinquires is that the found set of matching sites, information sources,or documents is often too small, i.e. too narrow, such as if too manysearch terms are entered within a string, or if the search terms are toonarrow in scope. A user is then typically required to perform one ormore subsequent searches, typically having different terms and/or fewerterms, in the hopes of finding a larger found set of desired sites andinformation.

Several structures and methods have been described for the searching andretrieval of information in a network environment.

J. Breese and C. Kadie, Methods and Apparatus for Tuning a Match BetweenEntities Having Attributes, U.S. Pat. No. 6,144,964, describe a matchingof “entities having attributes, some of which have associated values.The values of the attributes may be adjusted based on number of entitiesthat have values for a particular attribute so that the values decreaseas the number increases. The attributes of the entities may beharmonized and provided with default values so that entities beingmatched have common attributes defined by the union of the attributes ofthe entities being matched. The attributes of the entities may beexpanded and provided with default values so that the entities beingmatched have attributes that neither had originally. Match values may benormalized to provide a weight value which may be used to predict anattribute value of a new entity based on known attribute values of knownentities. The weight values may be tuned such that relatively highweights are amplified and relatively low weights are suppressed.”

B. Hazlehurst, S. Burke, and K. Nybakken, Intelligent Query System forAutomatically Indexing in a Database and Automatically CategorizingUsers, U.S. Pat. No. 6,289,353 B1, describe a system which “developsmultiple information spaces in which different types of real-worldobjects (e.g., documents, users, products) can be represented. Machinelearning techniques are used to facilitate automated emergence ofinformation spaces in which objects are represented as vectors of realnumbers. The system then delivers information to users based uponsimilarity measures applied to the representation of the objects inthese information spaces. The system simultaneously classifiesdocuments, users, products, and other objects. Documents are managed bycollators that act as classifiers of overlapping portions of thedatabase of documents. Collators evolve to meet the demands forinformation delivery expressed by user feedback. Liaisons act on thebehalf of users to elicit information from the population of collators.This information is then presented to users upon logging into the systemvia Internet or another communication channel. Mites handle incomingdocuments from multiple information sources (e.g., in-house editorialstaff, third-party news feeds, large databases, World Wide Web spiders)and feed documents to those collators which provide a good fit for thenew documents.”

V. Berstis and H. Rodriguez, Blocking Saves to Web Browser Cache Basedon Content Rating, U.S. Pat. No. 6,510,458 B1, describe a process inwhich a “user sets preference parameters that filter web page contentsfrom being stored in the cache. The preferences relate to the web page'scontents and attributes. Before caching the web page, the contents andattributes of the web page are filtered solely as a function of the webbrowser. Cache filters take a variety of forms, such as ratings filters,web page identifier filters, and key word filters, which scan accessedcontents of a web page for user selected terms. The filtered web page isthen blocked from entry in the browser's cache based on the filteringprocess. Conversely, a user sets preference parameters that filter webpage contents to override the block from cache preferences. The browserresponds by storing the filtered web pages that were previouslydesignated as web pages not to be cached.”

Other structures and methods for the searching and retrieval ofinformation include: Y. Freund et al., An Efficient Boosting Algorithmfor Combining Preferences, AT&T Labs, MIT Laboratory for ComputerScience; J. Shavlik et al., Building Intelligent Agents for Web-BasedTasks: A Theory-Refinement Approach, University of Wisconsin-Madison;and J. Shavlik, et al., Intelligent Agents for Web-based Tasks: AnAdvice-Taking Approach, University of Wisconsin-Madison.

Several other structures and methods provide background information inregard to the search and retrieval of information, such as: EuropeanPatent Application No. EP 1 288 795 A1, Query systems; D. Reed, P.Heymann, S. Mushero, K. Jones, J. Oberlander, and D. Banay,Computer-Based Communication System and Method Using Metadata Defining aControl Structure, U.S. Pat. No. 5,862,325; B. Hazlehurst, S. Burke, andK. Nybakken, Intelligent Query System for Automatically IndexingInformation in a Database and Automatically Categorizing Users, U.S.Pat. No. 5,974,412; J. Breese and C. Kadie, Methods and Apparatus forMatching Entities and for Predicting an Attribute of an Entity Based onan Attribute Frequency Value, U.S. Pat. No. 6,018,738; D. Donoho, D.Hindawi, and L. Lippincott, Method and Apparatus for Computed RelevanceMessaging, U.S. Pat. No. 6,256,664 B1; D. Donoho, D. Hindawi, and L.Lippincott, Inspector for Computed Relevance Messaging, U.S. Pat. No.6,263,362 B1; A. Lang and D. Kosak, IntegratedCollaborative/Content-Based Filter Structure Employing SelectivelyShared, Content-Based Profile Data to Evaluate Information Entities in aMassive Information Network, U.S. Pat. No. 6,308,175 B1, A. Lang and D.Kosak, Collaborative/Adaptive Search Engine, U.S. Pat. No. 6,314,420 B1;J. Breese and C. Kadie, Methods and Apparatus, Using ExpansionAttributes Having Default, Values, for Matching Entities and Predictingan Attribute of an Entity, U.S. Pat. No. 6,345,264 B1; D. Reed, P.Heymann, S. Mushero, K. Jones, J. Oberlander, and D. Banay,Computer-Based Communication System and Method Using Metadata Defining aControl-Structure, U.S. Pat. No. 6,345,288 B1; J. Breese and C. Kadie,Method and Apparatus, Using Attribute Set Harmonization and DefaultAttribute Values, for Matching Entities and Predicting an Attribute ofan Entity, U.S. Pat. No. 6,353,813 B1; D. Donoho, D. Hindawi, and L.Lippincott, Relevance Clause for Computed Relevance Messaging, U.S. Pat.No. 6,356,936 B1; E. Steeg, Coincidence Detection Method, Products andApparatus, U.S. Pat. No. 6,493,637 B1; System and Method for DataCollection, Evaluation Information Generation, And Presentation, U.S.Pat. No. 6,539,392 B1; Baudisch, P.; The Profile Editor: Designing aDirect Manipulative Tool for Assembling Profiles; Institute forIntegrated Information and Publication Systems IPSI, German NationalResearch Center for Information Technology GMD, Germany; J. Budzik etal.; User Interactions with Everyday Applications as Context forJust-in-time Information Access; Intelligent Information Laboratory,Northwestern University; J. Budzik et al.; Watson: Anticipating andContextualizing Information Needs; Northwestern University; E. Glover etal.; Improving Category Specific Web Search by Learning QueryModifications; NEC Research Institute, Princeton, N.J., EECS Department,University of Michigan, Ann Arbor, Mich., Information Sciences andTechnology, Pennsylvania State University; Pazzani et al., A Frameworkfor Collaborative, Content-Based and Demographic Filtering; Departmentof Information and Computer Science, University of California, Irvine;T. Bauer et al.; Real Time User Context Modeling for InformationRetrieval Agents, Computer Science Department, Indiana University; J.Shavlik et al.; An Instructable, Adaptive Interface for Discovery andMonitoring Information on the World-Wide Web; University ofWisconsin-Madison; J. Budzik et al.; Watson: An Infrastructure forProviding Task-Relevant, Just-In-Time Information; Department ofComputer Science, Northwestern University; and D. Nahl, Ethnography OfNovices' First Use Of Web Search Engines: Affective Control In CognitiveProcessing; Internet Reference Services Quarterly, vol. 3, no. 2, p.51-72, 1998.

It would be advantageous to provide a system and an associated methodwhich provides an enhancement to a search system, wherein the resultsfrom the search engine are refined or reorganized, based uponinformation from an identified secondary source. The development of sucha search enhancement system would constitute a major technologicaladvance.

It would also be advantageous to provide a system and an associatedmethod which provides an enhancement to a search system, whereininformation from an identified secondary source is integrated with asearch query, such that results from the search engine are refined ororganized, based upon the information from the identified secondarysource. The development of such a search enhancement system wouldconstitute a major technological advance.

In addition to search parameters which may be unique to a particularsearch, there are often parameters that are commonly relevant for aplurality of searches, such as relating to personalized informationregarding the user or to similarities between the subject matter of asearch. A user is often required to repeatedly input such parameters,along with other parameters that are unique to search.

Several structures and methods have been described for the searching andsorting of information, based on relevance, personal information, orprofiles.

J. Driscoll, Method and System for Searching for Relevant Documents froma Text Database Collection, Using Statistical Ranking, RelevancyFeedback and Small Pieces of Text, U.S. Pat. No. 5,642,502, describes asearch system and method “for retrieving relevant documents from a textdata base collection comprised of patents, medical and legal documents,journals, news stories and the like. Each small piece of text within thedocuments such as a sentence, phrase and semantic unit in the data baseis treated as a document. Natural language queries are used to searchfor relevant documents from the data base. A first search query createsa selected group of documents. Each word in both the search query and inthe documents are given weighted values. Combining the weighted valuescreates similarity values for each document which are then rankedaccording to their relevant importance to the search query. A userreading and passing through this ranked list checks off which documentsare relevant or not. Then the system automatically causes the originalsearch query to be updated into a second search query which can includethe same words, less words or different words than the first searchquery. Words in the second search query can have the same or differentweights compared to the first search query. The system automaticallysearches the text data base and creates a second group of documents,which as a minimum does not include at least one of the documents foundin the first group. The second group can also be comprised of additionaldocuments not found in the first group. The ranking of documents in thesecond group is different than the first ranking such that the morerelevant documents are found closer to the top of the list.”

T. Gerace, Method and Apparatus for Determining Behavioral Profile of aComputer User, U.S. Pat. No. 5,848,396, describes a computer networkmethod and apparatus which “provides targeting of appropriate audiencebased on psychographic or behavioral profiles of end users. Thepsychographic profile is formed by recording computer activity andviewing habits of the end user. Content of categories of interest anddisplay format in each category are revealed by the psychographicprofile, based on user viewing of agate information. Using the profile(with or without additional user demographics), advertisements aredisplayed to appropriately selected users. Based on regression analysisof recorded responses of a first set of users viewing theadvertisements, the target user profile is refined. Viewing by andregression analysis of recorded responses of subsequent sets of userscontinually auto-targets and customizes ads for the optimal end useraudience.”

F. Herz, System for Customized Electronic Identification of DesirableObjects, U.S. Pat. No. 6,029,195, describes “customized electronicidentification of desirable objects, such as news articles, in anelectronic media environment, and in particular to a system thatautomatically constructs both a “target profile” for each target objectin the electronic media based, for example, on the frequency with whicheach word appears in an article relative to its overall frequency of usein all articles, as well as a “target profile interest summary” for eachuser, which target profile interest summary describes the user'sinterest level in various types of target objects. The system thenevaluates the target profiles against the users' target profile interestsummaries to generate a user-customized rank ordered listing of targetobjects most likely to be of interest to each user so that the user canselect from among these potentially relevant target objects, which wereautomatically selected by this system from the plethora of targetobjects that are profiled on the electronic media. Users' target profileinterest summaries can be used to efficiently organize the distributionof information in a large scale system consisting of many usersinterconnected by means of a communication network. Additionally, acryptographically-based pseudonym proxy server is provided to ensure theprivacy of a user's target profile interest summary, by giving the usercontrol over the ability of third parties to access this summary and toidentify or contact the user.”

A. Lang and D. Kosak, Collaborative/Adaptive Search Engine, U.S. Pat.No. 6,314,420 B1, describe a search engine system “for a portal site onthe internet. The search engine system employs a regular search engineto make one-shot or demand searches for information entities whichprovide at least threshold matches to user queries. The search enginesystem also employs a collaborative/content-based filter to makecontinuing searches for information entities which match existing wirequeries and are ranked and stored over time in user-accessible, systemwires corresponding to the respective queries. A user feedback systemprovides collaborative feedback data for integration with contentprofile data in the operation of the collaborative/content-based filter.A query processor determines whether a demand search or a wire search ismade for an input query.”

D. Kravets, L. Chiriac, J. Esakov, and S. Wan, Search Data Processor,U.S. Pat. No. 6,363,377 B1, describe a “tool to be used with a searchengine for a information management system includes methods forrefining, filtering, and organizing search queries and search results. Aquery tuner in the tool allows a user to automatically reformulate aquery in order to find a reasonable number of matching documents fromthe search engine by selectively modifying individual search terms to beweaker or stronger and concurrently requesting a plurality of searches,each with a respectively different modified query. The tool also uses adynamic filter which employs a dynamic set of record tokens to restrictthe results of an arbitrary search query to selectively include orexclude records which correspond to the set of record tokens. The toolalso includes a results organizer which aids the user in understandingand visualizing a large number of matching documents returned inresponse to a search query by clustering like items returned from thesearch. The query tuner, dynamic filter and results organizer may beused individually or in conjunction. The searched information managementsystem may be consolidated or distributed and may span a globalinformation network such as the Internet.”

P. Biffar, Self-Learning and Self-Personalizing Knowledge Search EngineThat Delivers Holistic Results, U.S. Pat. No. 6,397,212 B1, describes asearch engine which “provides intelligent multi-dimensional searches, inwhich the search engine always presents a complete, holistic result, andin which the search engine presents knowledge (i.e. linked facts) andnot just information (i.e. facts). The search engine is adaptive, suchthat the search results improve over time as the system learns about theuser and develops a user profile. Thus, the search engine is selfpersonalizing, i.e. it collects and analyzes the user history, and/or ithas the user react to solutions and learns from such user reactions. Thesearch engine generates profiles, e.g. it learns from all searches ofall users and combines the user profiles and patterns of similar users.The search engine accepts direct user feedback to improve the nextsearch iteration One feature of the invention is locking/unlocking,where a user may select specific attributes that are to remain lockedwhile the search engine matches these locked attributes to all unlockedattributes. The user may also specify details about characteristics,provide and/or receive qualitative ratings of an overall result, andintroduce additional criteria to the search strategy or select a searchalgorithm. Additionally, the system can be set up such that it does notrequire a keyboard and/or mouse interface, e.g. it can operate with atelevision remote control or other such human interface.”

G. Cullis, Personalized Search Methods, U.S. Pat. No. 6,539,377 B1,describes a “method of organizing information in which the searchactivity of previous users is monitored and such activity is used toorganize articles for future users. Personal data about future users canbe used to provide different article rankings depending on the searchactivity and personal data of the previous users.”

Other structures and methods have been described which providebackground information regarding the searching and sorting ofinformation, based on relevance, personal information, or profiles, suchas: J. Pitkow et al.; Personalized Search, Communications of the ACM,vol. 45, no. 9, p. 50-5, September 2002; J. McGowan et al., Who Do YouWant To Be Today? Web Personae for Personalised Information Access;Adaptive Hypermedia and Adaptive Web-Based Systems. Second InternationalConference, AH 2002. Proceedings (Lecture Notes in Computer Science Vol.2347), p. 514-17, 2002; S. Kalajdziski et al.; IntelligentRecommendation in Digital Library, Proceedings of the IASTEDInternational Conference Intelligent Systems and Control, p. 408-12,ACTA Press, Anaheim, Calif., USA, 2001; L. Kerschberg et al., A SemanticTaxonomy-Based Personalizable Meta-Search Agent, Proceedings of theSecond International Conference on Web Information Systems Engineering,vol. 1, p. 41-50; IEEE Comput. Soc., Los Alamitos, Calif., USA, 2002; C.Dichev, A Framework for Context-Driven Web Resource Discovery, Modelingand Using Context, Third International and Interdisciplinary Conference,Context 2001, Proceedings (Lecture Notes in Artificial Intelligence,vol. 2116), p. 433-6, Springer-Verlag, Berlin, Germany, 2001; X. Meng etal., Feasibility of Adding Filtering Process in Web Browser to ImproveWeb Search Accuracy, Proceedings of the International Conference onParallel and Distributed Processing Techniques and Applications, PDPTA'2000, vol. 4, p. 1809-15, CSREA Press, Athens, Ga., USA, 2000; K. Kimet al., Development of a Personalized Link-Based Search Engine UsingFuzzy Concept Network, Journal of KISS: Computing Practices, vol. 7, no.3, p. 211-19, Korea Inf. Sci. Soc., June 2001; C. Yang et al., A HybridDocument Clustering for a Web Agent, Journal of KISS: Software andApplications, vol. 28, no. 5, p. 422-30, Korea Inf. Sci. Soc., May 2001;K. Kim et al.; A Personalized Web Search Engine Using Fuzzy ConceptNetwork with Link Structure; Proceedings Joint 9th IFSA World Congressand 20th NAFIPS International Conference (Cat. No. 01TH8569), vol. 1, p.81-6; IEEE, Piscataway, N.J., USA; 2001; A. Scime et al.; WebSifter: AnOntology-Based Personalizable Search Agent for the Web; Proceedings 2000Kyoto International Conference on Digital Libraries Research andPractice, p. 203-10; IEEE Comput. Soc., Los Alamitos, Calif., USA; 2000;Z. Wei-Feng et al., Personalizing Search Result Using Agent, Mini-MicroSystems, vol. 22, no. 6, p. 724-7, Mini-Micro Syst., China, June 2001;P. Chen et al., An Information Retrieval System Based on a User Profile,Journal of Systems and Software, vol. 54, no. 1, p. 3-8, Elsevier, Sep.30, 2000; X. Meng et al., Personalize Web Search Using Information OnClient's Side, Fifth International Conference for Young ComputerScientists, ICYCS'99, Advances in Computer Science and Technology, vol.2, p. 985-92; Int. Acad. Publishers, Beijing, China, 1999; P. Chen etal.; A Personalized Information Retrieval System; ComputationalIntelligence for Modelling, Control and Automation, Intelligent ImageProcessing, Data Analysis and Information Retrieval (Concurrent SystemsEngineering Series, vol. 56), p. 247-53, IOS Press, Amsterdam,Netherlands, 1999; S. Laine-Cruzel et al., Improving InformationRetrieval by Combining User Profile and Document Segmentation,Information Processing & Management, vol. 32, no. 3, p. 305-15;Elsevier, May 1996; D. Boley et al., Document Categorization and QueryGeneration on the World Wide Web Using WebACE; Department of ComputerScience and Engineering, University of Minnesota; and A. Pretschner,Ontology Based Personalized Search, Dipl.-Inform., RWTH Aachen, Germany,1998.

Other documents provide background information regarding advancements insearch engine structures and processes, such as: European PatentApplication No. EP 1 072 982 A2, Method and System for Similar WordExtraction And Document Retrieval; European Patent Specification No. EP1 095 326 B1, A Search System and Method for Retrieval of Data, and theUse Thereof in a Search Engine; European Patent Application No. EP 1 284461 A1, Meta-Document Management System With User DefinablePersonalities; European Patent Application No. EP 1 288 795 A1, Querysystems; A. Lang and D. Kosak, System and Method Employing IndividualUser Content-Based Data and User Collaborative Feedback Data to Evaluatethe Content of an Information Entity in a Large Information.Communication Network, U.S. Pat. No. 5,983,214; A. Lang and D. Kosak,Multi-Level Mindpool System Especially Adapted to Provide CollaborativeFilter Data for a Large Scale Information Filtering System, U.S. Pat.No. 6,029,161; M. Tso, D. Romrell, And D. Gillespie, System forDistributing Electronic Information to a Targeted Group of Users, U.S.Pat. No. 6,047,327; G. Culliss, Personalized Search Methods, U.S. Pat.No. 6,182,068 B1; A. Lang and D. Kosak, Integrated Collaborative/Content-Based Filter Structure Employing Selectively Shared,Content-Based Profile Data to Evaluate Information Entities in a MassiveInformation Network; U.S. Pat. No. 6,308,175 B1; D. Chen, CooperativeTopical Servers With Automatic Prefiltering and Routing, U.S. Pat. No.6,349,307 B1; D. Judd, P. Gauthier, and J. Baldeschwieler, Method andApparatus for Retrieving Documents Based on Information other thanDocument Content, U.S. Pat. No. 6,360,215 B1; K. Risvik, Search Systemand Method for Retrieval of Data, and the Use Thereof in a SearchEngine, U.S. Pat. No. 6,377,945 B1; E. Marwell and R. Pines,Personalized Assistance System and Method, U.S. Pat. No. 6,404,884 B1;A. Weissman and G. Elbaz, Meaning-Based Information Organization andRetrieval, U.S. Pat. No. 6,453,315 B1; J. Lee, L. Morgenstern, M.Pedlaseck, E. Schonberg, and D. Wood, System and Method for Collectingand Analyzing Information About Content Requested in a Network (WorldWide Web) Environment, U.S. Pat. No. 6,466,970 B1; S. Edlund, M. Emens,R. Kraft, and P. Yim, Labeling and Describing Search Queries for Reuse,U.S. Pat. No. 6,484,162 B1; J. Zhang and M. Ott, Method and Apparatusfor Active Information Discovery and Retrieval, U.S. Pat. No. 6,498,795B1; L. Nikolovska, J. Martino, and A. Camplin, Search User Interfacewith Enhanced Accessibility and Ease-Of-Use Features Based on VisualMetaphors, U.S. Pat. No. 6,505,194 B1; M. Bowman-Amuah, PiecemealRetrieval in an Information Services Patterns Environment, U.S. Pat. No.6,550,057 B1; Callan, J. et al.; Document Filterinq with InferenceNetworks; Computer Science Department, University of Massachusetts;Goker, A.; Capturing Information Need by Learning User Context; Schoolof Computer and Mathematical Sciences; The Robert Gordon University;Chen, L. et al.; WebMate: A Personal Agent for Browsing and Searching;The Robotics Institute, Carnegie Mellon Institute; Sep. 30, 1997;Cooley, R. et al.; Web Mining: Information and Pattern Discovery on theWorld Wide Web; Department of Computer Science and Engineering,University of Minnesota; Simons, J.; Using a Semantic User Model toFilter the World Wide Web Proactively; Nijmegen Institute for Cognitionand Information, University of Nijmegen, The Netherlands; Tanudjaja, F.et al.; Persona: A Contextualized and Personalized Web Search;Laboratory of Computer Science at MIT, Cambridge, Mass.; Jun. 1, 2001;Yan, T. et al.; SIFT—A Tool for Wide-Area Information Dissemination;Department of Computer Science, Stanford University, Feb. 16, 1995;Bianchi-Berthouze, N.; Mining Multimedia Subjective Feedback; Journal ofIntelligent Information Systems: Integrating Artificial Intelligence andDatabase Technologies, vol. 19, no. 1, p. 43-59; Kluwer AcademicPublishers; July 2002; Widyantoro, D. H. et al.; A fuzzy Ontology-BasedAbstract Search Engine and Its User Studies; 10th IEEE InternationalConference on Fuzzy Systems. (Cat. No.01CH37297), vol. 2, p. 1291-4;IEEE, Piscataway, N.J., USA; 2001; Tanudjaja, F. et al.; Persona: AContextualized and Personalized Web Search; Proceedings of the 35thAnnual Hawaii International Conference on System Sciences, p. 1232-40;IEEE Comput. Soc, Los Alamitos, Calif., USA; 2002; Widyantoro, D. H. etal.; Using Fuzzy Ontology for Query Refinement in a PersonalizedAbstract Search Engine; Proceedings Joint 9th IFSA World Congress and20th NAFIPS International Conference (Cat. No. 01TH8569), vol. 1, p.610-15; IEEE, Piscataway, N.J., USA; 2001; Ho, M. et al.; A GA-BasedDynamic Personalized Filtering for Internet Search Service onMulti-Search Engine; Canadian Conference on Electrical and ComputerEngineering 2001, Conference Proceedings (Cat. No.01TH8555) vol. 1, p.271-6; IEEE, Piscataway, N.J., USA; 2001; Pogaenik, M. et al.; LayeredAgent System Architecture for Personalized Retrieval of Information fromInternet; Signal Processing X Theories and Applications. Proceedings ofEUSIPCO 2000. Tenth European Signal Processing Conference, vol. 1, p.421-4; Tampere Univ. Technology, Tampere, Finland; 2000; Ho, M. et al.;An Agent-Based Personalized Search on a Multi-Search Engine Based onInternet Search Service; Intelligent Data Engineering andAutomated—IDEAL 2000, Data Mining, Financial Engineering, andIntelligent Agents, Second International Conference, Proceedings(Lecture Notes in Computer Science Vol. 1983), p. 404-9;Springer-Verlag, Berlin, Germany; 2000; Wei-Feng, Z. et al.;Personalizing Search Result Using Agent; Mini-Micro Systems, vol. 22,no. 6, p. 724-7; Mini-Micro Syst., China; Overmeer, M.A.C.J.; MyPersonal Search Engine; Computer Networks, vol. 31, no. 21, p. 2271-9;Elsevier, Nov. 10, 1999; Pretschner, A. et al.; Ontology BasedPersonalized Search; Proceedings 11th International Conference on Toolswith Artificial Intelligence, p. 391-8; IEEE Comput. Soc., Los Alamitos,Calif., USA, 1999; Lee, E. S. et al.; Agent-Based Support forPersonalized Information with Web Search Engines; Design of ComputingSystems: Cognitive Considerations. Proceedings of the SeventhInternational Conference on Human-Computer Interaction (HClInternational '97), vol. 2, p. 783-6; Elsevier, Amsterdam, Netherlands,1997; and Berger, F. C. et al., Personalized Search Support forNetworked Document Retrieval Using Link Inference, Database and ExpertSystems Applications. 7th International Conference, DEXA '96Proceedings, p. 802-11, Springer-Verlag, Berlin, Germany, 1996.

It would be advantageous to provide a system and an associated methodwhich provides an enhancement to a search system, wherein a user mayspecify one or more search parameters, and wherein the user-specifiedsearch parameters are integrated into a search query, based on thesubject matter of that query. The development of such a searchenhancement system would constitute a major technological advance.

As well, it would be advantageous to provide a system and an associatedmethod which provides an enhancement to a search system, wherein a usermay specify one or more search parameters, and wherein theuser-specified search parameters are integrated into a search query,based on the subject matter of that query, in which the subject matteris either explicitly determined or is implicitly determined, based uponuser input. The development of such a search enhancement system wouldconstitute a further technological advance.

Furthermore, it would be advantageous to provide a system and anassociated method which provides an enhancement to a search system, inwhich general search parameters are solicited from a user before aparticularized search, and wherein the solicited search parameters areassociated with the user and are available for automatic integrationinto future particularized searches initiated by the user. Thedevelopment of such a search enhancement system would constitute afurther technological advance.

In addition, it would be advantageous to provide a system and anassociated method which provides an enhancement to a search system, inwhich general search parameters are solicited from a user before orafter a particularized search, and wherein the solicited searchparameters are associated with user selectable editorial content, suchas for delivery to the user and/or to other recipients, and areavailable for automatic integration into future particularized searches,such as initiated by the user or by other recipients that are associatedwith the user USR, such as a network of friends, family, peers,students, neighbors, people or entities within a zip code region, and/orbusiness associates. The development of such a search enhancement systemwould constitute a further technological advance.

SUMMARY OF THE INVENTION

The system and method comprises enhancement of results for a searchengine, wherein the results from the search engine are refined orreorganized, based upon information from an identified secondary source.The results obtained using a conventional search are compared againstthe identified secondary source, e.g. a ratings service, and arefiltered and/or sorted appropriately. In some embodiments,identification of the secondary source, such as a ratings servicecomprising information which may supplement the subject of a searchquery, is based upon information entered by the user. In alternateembodiments, the secondary source is associated with a user, as part ofgeneral user-specified search parameters, wherein one or more parametersare consulted automatically for searches for appropriate subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of a system for customizing results receivedfrom a search engine, wherein the customization comprises refinement ofthe search results based upon information received from an externalsource;

FIG. 2 is a schematic view of an alternate system for customizingresults received from a search engine, wherein the customizationcomprises an organization of the search results based upon informationreceived from an external source;

FIG. 3 is a schematic diagram of user identification, i.e. selection, ofan external source within a system for further acting upon resultsreceived from a search engine;

FIG. 4 is a schematic view of a system for acting upon results receivedfrom a search engine implemented within an integrated application;

FIG. 5 is a schematic view of an alternate modular system forcustomizing results received from a search engine implemented inconjunction with a conventional search engine;

FIG. 6 is a functional block diagram of operation within a system forcustomizing results received from a search engine implemented within anintegrated application;

FIG. 7 is a functional block diagram of operation within an alternatemodular system for customizing results received from a search engineimplemented in conjunction with a conventional search engine;

FIG. 8 is a flowchart showing a process for identification of one ormore external sources, and for refining search results based uponinformation received from the identified sources;

FIG. 9 is a schematic diagram of an enhanced primary search inputscreen;

FIG. 10 is a schematic diagram of an enhanced search system sourceselection screen;

FIG. 11 is a schematic diagram of a primary search result screen furthercomprising enhanced source solicitation control;

FIG. 12 shows user specification of secondary search parameters;

FIG. 13 is a schematic diagram of an enhanced search parameter andsubject validities;

FIG. 14 is a detailed schematic diagram of an exemplary enhanced searchparameter and subject validities;

FIG. 15 is a functional block diagram of an enhanced search systemcomprising personal search parameters; and

FIG. 16 is a flow chart of an enhanced search process comprisingpersonal search parameters.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

FIG. 1 is a schematic view of a system 10 a for acting upon, i.e.enhancing or customizing 22 (FIG. 3), results 14 received from a searchengine 12, wherein the customization 22 comprises refinement 22 a of thesearch results 14 based upon information 18 received 20 from an externalsource 16. FIG. 2 is a schematic view of an alternate system 10 b forcustomizing 22 results received from a search engine 14, wherein thecustomization 22 comprises an organization, i.e. ranking 22 b, of thesearch results 14, based upon information 18 received 20 from anexternal source 16.

The search enhancement system 10 improves current search methodologies,by refining 22 a and/or organizing 22 b the results 14 of a searchengine 12, in compliance with information 18 from one or more sources16. In a typical system embodiment 10, a user USR (FIG. 3) selects 33(FIG. 3) an information source 16 to be consulted by a searchapplication 12, in the process of performing a search 24.

In some system embodiments 10, the results 14 of a search 24 are furtherrefined 22 a and/or organized 22 b, based upon information 18 receivedfrom an external source 16. For example, in a user-initiated search 13for lodging in Austin, Tex., a user specified source 16 may preferablycomprise rating information 18 of lodgings, e.g. such as availablethrough American Automobile Association, Inc. (AAA). The ratinginformation 18, from the external source 16, e.g. AAA, is then used torefine 22 a and/or organize 22 b the results 14 of a general search 24for any lodging that otherwise meets the search parameters 106, 108,e.g. 108 a, 108 b (FIG. 9, FIG. 10, FIG. 11) within a search query 13.Results from a conventional search engine 12 may therefore be refined 22a and/or reorganized 22 b, based on data 18 independently maintained bya ratings service 16.

In alternate system embodiments 10, information 18 received from anexternal source 16 is integrated within a search query 13, such that thesearch 24 is enhanced by the information 18, whereby the results 14 ofthe search 24 may be inherently refined 22 a and/or organized 22 b as afunction of the information 18 received from an external source 16. Forexample, information 18 received from a user-selected source 16 may beconsulted when performing a search 24, such that a set of one or moresearch results 14 complies with a search query 13 comprising both searchparameters 108, 106 entered by a user USR, in addition to meetingparameters imposed by the information 18 received from the externalsource 16.

For example, in a similar user-initiated search 13 for lodging inAustin, Tex., a user specified source 16 which comprises ratinginformation 18 of lodgings can alternately be included in the search 24,i.e. to refine or organize the search results 14, whereby the results ofthe general search 24 meet the user-specified search parameters 108,106, and also comply with rating information 18 provided by a selectedratings service 16.

In some system embodiments 10, the external information 18 can becombined with other external information 18. In the above example, in auser-initiated search 13 a for lodging in Austin, Tex., wherein a userspecified source 16 comprises rating information 18 of lodgings, therating information 18 can be combined with policy information 18, suchas to further refine or organize the search results 14, to lodging whichis approved by a secondary external source 16, e.g. an accountingdepartment, associated with the user USR, to be within a specified costper diem amount.

Supplementary external information 18 may also correspond to people orentities which are associated with the user USR, e.g. such as a networkof friends, family, peers, students, neighbors, people or entities witha zip code region, and/or business associates. For example a user USRmay be interested in the enhanced results 40 based on rankinginformation 18 from:

-   -   Expert entities, e.g. Zagats, AAA, or a movie critic;    -   Celebrities, e.g. Michael Jordan, John Cusack, or Sarah Michelle        Gellar; or    -   People similar to the user USR, i.e. “people like me”, such as        local people of a similar age and/or education level, immediate        friends or friends of friends.

In system embodiments 10 in which information 18 from an external source16 is combined with information 18 from one or more other externalsources 16, the enhanced search results 40 preferably yield a compositerefinement or ranking 22, for a user USR. For example, in a search forlocal services or people, e.g. a roofing contractor, a user USR cancombine a general search for local contractors within a desired area,e.g. within a city, county, or zip code, and can rank the results basedon information from a ratings service 18, and/or with information 18from other external sources 16, such as review information from people,e.g. such as neighbors who have used roofing contractors, other usersUSR, recipients RCP (FIG. 3), and/or experts.

FIG. 3 is a schematic diagram 30 of user identification, i.e. selection33 of an external source 16 within a system 10 for further acting 22upon results 14 received from a search engine 12. A user USR typicallyinteracts with the system 10 through a terminal 32, such as a personalcomputer, laptop computer, or other networked device, such as a personaldigital assistant, a network enabled portable phone, or other wired orwireless device.

Through user identifier input 33, the system 10 determines, i.e.identifies 34 one or more selected external sources 16, either directly,e.g. through explicit entry 33 of the identity of a source 16, orindirectly, e.g. through an implicit determination of an identity of asource 16, such as through the determination of subject matter of asearch query 13, and a determination of one or more sources 16 that haveinformation 18 which pertains to the determined subject matter.

The system 10 retrieves information 38 from an external source 16, suchas though a an information query 36. Based upon data received 38 from aselected source 16, the system 10 returns 41 enhanced search results 40,e.g. such as by returning 41 a to the user USR, through the terminal 32,and/or by delivering results 41 b to one or more recipients RCP, such asthrough terminals 32.

In some system embodiments 10, recipients RCP are explicitly determinedby the user USR. In other system embodiments 10, recipients RCP may beinferentially determined by the user USR, such as comprising one or morerecipients RCP that are associated with the user USR, e.g. such as anetwork of friends, family, peers, students, neighbors, people orentities with a zip code region, and/or business associates. Forexample, a query 13 from a user USR regarding museums in Paris, Francemay be refined 22 a or ranked 22 b, and then may be forwarded 40 b torecipients RCP, such as to recipients RCP that choose 86 (FIG. 7) toreceive 41 b, or are chosen to receive 41 b, the information.

In some system embodiments 10, recipients RCP may be inferentiallydetermined by the search parameters or search results, such ascomprising a one or more recipients RCP for which editorially ranked 22a or sorted 22 b content 40 is determined to be valid. For example, aquery 13 from a user USR regarding museums in Paris may be refined 22 aor ranked 22 b, and then may be forwarded 40 b to recipients RCP, suchas to recipients RCP that have expressed interest in art, and/or France,such as through recipient input 86 (FIG. 7).

The search enhancement system 10 may therefore be preferably used toprovide editorially refined 22 a or ranked 22 b results, as a result ofa user selectable editorial search 13,22, for delivery to the user USRand/or to one or more recipients RCP.

As discussed above, in some system embodiments 10, the results 14 of ageneral search query 13 are acted upon 22 by the information 18 from theselected source 16, while in alternate system embodiments 10, theinformation 18 from the selected source 16 is integrated within thequery 13, to provide search results 14 that correspond to both thegeneral search parameters 108, 106, as well as to the supplementalinformation 18 from the selected source 16.

User Source Selection and Delivery of Enhanced Search Query Results.FIG. 4 is a schematic view 42 of a system 10 c for acting upon results14 received from a search engine 12 implemented within an integratedsearch structure 44, i.e. an enhanced search engine 44. FIG. 5 is aschematic view 60 of an alternate modular system 10 d for customizingresults 14 received from a search engine 12 implemented in conjunctionwith a modular application component 46.

As seen in FIG. 4, system source identification 34 and informationprocessing 22 in a system 10 c are readily implemented within anapplication component 46 which is integrated 44 with a search engine 12.When a user USR initiates 52 a search 24, the application component 46shown in FIG. 4 provides source identification 34, based upon userselection 33, and either acts 22 upon the results 14 of a general query13 that meets user search criteria 106, 108 (FIG. 9), or alternatelymodifies the query 13, based upon information 18, e.g. 18 b, from one ormore selected sources 16, e.g. 16 b.

As seen in FIG. 5, the system source identification 34 and informationprocessing 22 in a system 10 d are implemented within a modular, i.e.distinct, application component 46 which is in associated with adiscrete search engine 12. For example, an application component 46 forsource identification 34 and information processing 22 may operate as aseparate component in relation with an existing search engine 12,whereby information 18 from a selected source 16 is either integratedinto a search query 13, e.g. such as through additional Boolean stringelements, or is used to process 22 the results 14 of a query 13.

System Operation. FIG. 6 is a functional block diagram 70 of operationwithin a system 10 e for acting upon results 14 received from a searchengine 12 implemented within an integrated search structure 44. FIG. 7is a functional block diagram 82 of operation within an alternatemodular system 10 f for customizing results 14 received from a searchengine 12 implemented in conjunction with a modular applicationcomponent 46.

FIG. 8 is a flowchart showing an exemplary process 90 for an enhancedsearch system 10, comprising identification 33 of one or more externalsources 16, and the enhancement 22 of search results 14 based uponinformation 18 received from one or more identified sources 18.

As seen in FIG. 6 and FIG. 7, a user USR interacts 71 with the enhancedsearch system 10, typically between a user terminal 32 and anapplication module 46. Typical interactions 71 between a user terminal32 and the application module 46 comprise search initiation 52, thereturn of standard, i.e. non-enhanced, search results 73, source prompts74, source identification inputs 33, and/or the return 41 a (FIG. 3) ofenhanced results 40.

In some embodiments of the enhanced search system 10, as seen in FIG. 7,one or more recipients RCP at terminals 32 may also interact 86 with theapplication module 46. Typical interactions 86 between a recipientterminal 32 and the application module 46 comprise establishment ofrelationships 87, e.g. such as between users USR and recipients RCP,and/or an input of preferences or interest in the receipt 41 b ofenhanced system content 40.

The application module 46 has access 72, e.g. 72 a-72 n, to one or moresources 16, e.g. 16 a-16 n, having associated data 18, e.g. 18 a-18 n.The sources 16 a-16 n are typically accessible across a network, e.g.such as but not limited to the Internet. In some system applications 10,the associated data 18 is sent 72 to the application module 46 beforesource identification 33 from a user USR, such that information 18associated with a source 16 is internally available within theapplication module 46. In other system applications, the associated data18 is sent 72 to the application module 46 upon source identification 33from a user USR, wherein information associated with a source 16 istypically queried 36 (FIG. 5) and retrieved 38 by the application module46.

As seen in FIG. 6 and FIG. 7, a search engine 12 is associated withapplication module 46. The search engine 12 has access 76, e.g. 76 a-76k, to one or more external sites, sources or documents 78, e.g. 78 a-78k, having associated content 80, e.g. 80 a-80 k. The search engine 12typically retrieves information content 80 that corresponds to a searchquery 13.

In the exemplary process 90 shown in FIG. 8, when a user USR initiates asearch query process 52, the application module 46 typically solicits 74the identification 33 of one or more sources 16 comprising data 18 whichmay be used to enhance the value of a search 24, e.g. to improve thequality and/or ordering of search results 14. In some system embodiments10, a source solicitation 74 comprises a choice of one or moreselectable sources 16, typically comprising sources 16 that are eitherexplicitly available to the user USR, or are implicitly determined, e.g.such as travel related sources 16 if a search query 13 comprises one ormore search parameters 108 within a search string 106 (FIG. 9 to FIG.11), which indicate that the user USR is searching for lodging or travelaccommodations.

Upon a receipt 33 of source identification from a user USR, theapplication module 46 typically sends a data query 36 to any identifiedsources 16, if the available data 18 from an identified source 16 is notyet available. Upon a data query 36, the data 18 is sent from anidentified source 16, either to be included in a search query 13, or tobe used in the processing 22 of search results 14. The applicationmodule 46 produces 22 the enhanced results 40, which are then sent 41 ato the user terminal 32, and/or sent 41 b to recipients RCP.

Conventional search engines typically compare input search terms 108against content or metadata 80, to identify displayable results. Somesearch processes also allow for refined searching in input terms 108,against particular identified types of content or metadata 80. Forexample, when performing a patent search, a user USR is able to enter“SN” to indicate that subsequent search terms 108 should be appliedagainst serial number metadata. Furthermore, some of the conventionalsearch engines permit comparison of input search terms against full orpartial text.

When applying conventional search technology, users USR typically obtainseveral pages of search results for any given search query,necessitating an extended period of review. For example, a commonproblem which is often encountered with conventional search queries isthat the found set 138 (FIG. 11) of matching sites or informationsources 78 is often too large, e.g. such as if too few search terms 108(FIG. 11) are entered within a string 106 (FIG. 11), or if the searchterms 108 are too general. A user USR must often either manually browsethrough a large number of found content 80 to find relevant sites 78, ormust perform a different search 24, typically having different terms 108and/or additional terms 108, in the hopes of more accurately finding thedesired sites 78 and information 80.

A similar problem that is also encountered with conventional searchinquires is that the found set 138 of matching sites or informationsources 78 is often too small, e.g. such as if too many search terms 108are entered within a string 106, or if the search terms 108 are toonarrow in scope. A user USR then is typically required to performanother search, typically having different terms 108 and/or less terms108, in the hopes of finding a larger found set 138 of desired sites 78and information 80.

FIG. 9 is a schematic view 100 of an enhanced primary search user entryscreen 102 for a search engine 12, in which a user USR may preferablyselect one or more sources 16 at the same time as primary searchparameters 108, e.g. 108 a, 108 b, are entered. As seen in FIG. 9, aninput screen 102 comprises a parameter input window 104, wherein a userUSR can input one or more search parameters 108, e.g. 108 a, 108 b, suchas within a Boolean string format 106. If a primary search 24 isdesired, i.e. without a selection of secondary sources 16, a searchcontrol 110 may preferably be activated, such that the primary search 24is based only upon the primary search parameters 108, e.g. 108 a, 108 b,such as within a search string 106.

The enhanced primary search user entry screen 102 shown in FIG. 9 alsocomprises secondary source selection 112, comprising one or more subjectsources 116 a-116 j within one or more search subject groups 114 a-114k. For example, within a travel subject group 114 a, one or more travelsubject sources 116 a-116 j are selectable by the user USR, such thatcorresponding sources 16 are referenced in association with a search 24corresponding to the primary search parameters 108. A search subjectgroup 114 may comprise any of a wide variety of selectable subjects 114,such as but not limited to travel, shopping, business, technology, orpersonal sources 114. The displayed selection of subjects 114 andsubject sources may reflect general subject areas, i.e. for general useraudiences, or may alternately reflect more specialized professional orpersonal interests, such as internet-based opinion, review, and/orratings sources 16.

The search subject groups 114 a-114 k shown in FIG. 9 also comprisecorresponding options control 118 a-118 k, such as to add or subtractdesired source choices 116, and/or to select options based upon a source16, such as to select a desired rating level of lodging, e.g. 4 stars,based upon a selected source 16.

As seen in FIG. 9, the source selectors 116 allow selection of one ormore secondary sources 16. In some system embodiments 10, information 18associated with a source selection 116 accompanies the general searchparameters 106, 108 during a search 24. In alternate system embodiments10, information 18 associated with a source selection 116 is used toenhance 22 the results 20 of a general search 24 that is based upon theparameters 106, 108.

In some system embodiments, preliminary source selectors 116 compriseselectable choices of external sources 16, such as ranking sources 16,such as a ratings service 16 for restaurants, e.g. zagats.com, availablethrough Zagat Survey LLC, of New York, N.Y. When searching for arestaurant using a search engine 12, a user USR may find it helpful tofilter 22 a or sort 22 b results based on a rating from a ratingsservice 16. More specifically, the user USR can search for and displayonly restaurants with a Zagats rating higher than two, or the user USRmay search for all restaurants meeting a specified criteria, and sortall restaurant hits based on the Zagats rating. Similarly, whensearching for lodging using a search engine 12, a user USR may find ithelpful to filter 22 a or sort 22 b results based on a rating from atravel related ratings service 16, e.g. such as ratings provided byAmerican Automobile Association, Inc. (AAA).

Some system embodiments 10 allow express entry by the user USR ofinformation in a search string, such as within the primary input window104, to enable identification of such a source. In an alternativeimplementation, a source, e.g. Zagats or AAA, and an appropriate ratingfor a source 16, e.g. a Zagats rating equal to 2, may be associated witha user USR as a part of general user-specified search parameters 148,e.g. 148 a (FIG. 12), in which one or more user-specified parameters 148may be consulted automatically for searches of appropriate subjectmatter. In alternate system embodiments 10, the preliminary sourceselectors 116 comprise selectable choices of user-defined sources 16,such as to include one or more-user-selected parameters 148 (FIG. 12).

In some embodiments, the selected 116 external sources 16 are includedalong with the primary search parameters 108. In alternate embodiments,selected external sources 16 are referenced to refine 22 a and/orreorganize 22 b results 14 of a search 24 based upon the primary searchparameters 108 within the search string 106, i.e. the search engine 12conducts a search 24, based upon parameters 106, 108, wherein theresults of a search 24 typically include all sites or sources 78 whichmeet the search parameter set.

FIG. 10 is a schematic diagram 120 of an enhanced search system sourceselection screen 122. As described above, a user USR may initiate 52 asearch 24, such as based upon one or more search parameters 108 within asearch string 106. In some embodiments of an enhanced search system 10,a solicitation, i.e. source prompt 74 may be made, such that a user USRcan select one or more sources 16 which can be used to refine 22 aand/or organize 22 b the results of a search 24.

As seen in FIG. 10, the enhanced search system source selection screen120 preferably displays entered search parameters 106, 108, and may alsodisplay a search subject 124, e.g. such as but not limited to travel,cuisine, technical, biographical, cultural, or business subjects. Thesearch subject 124 may be determined either explicitly or implicitlyfrom the search parameters 106, 108, or may otherwise be selected ordetermined, such as by user subject selection control 125. The systemsource selection screen 122 shown in FIG. 10 also comprises a secondarysource selection 112, from which one or more subject selections 116a-116 j may be made by a user USR. The exemplary subject selectionoption 114 a shown in FIG. 10 corresponds to one or more travel relatedsource selections 116, e.g. 116 a-116 j, based on the determined subject124. The enhanced search system source selection screen 120 alsocomprises a refine results control 126 and an enhanced search control128, whereby a user USR can control search refinement or organization22, based upon source selections 116.

The secondary source selection 112, as shown in FIG. 10, may alternatelycorrespond to people or entities which are associated with the user USR,e.g. such as a network of friends, family, peers, students, neighbors,people or entities with a zip code region, and/or business associates.For example, the secondary source selection 112 may provide systemaccess to external information or input 18 from one or more recipientsRCP that are associated with the user USR. In another example, thesecondary source selection 112 may provide system access to externalinformation or input 18 from:

-   -   Expert entities e.g. Zagats, AAA, or a movie critic;    -   Celebrities, e.g. Michael Jordan, John Cusack, or Sarah Michelle        Gellar; and/or    -   People similar to the user USR, i.e. “people like me”, such as        local people of a similar age and/or education level, immediate        friends or friends of friends.

FIG. 11 is a schematic diagram 130 of a primary search result screen 132further comprising enhanced source solicitation control 126, 128. Asdescribed above, a search 24 which comprises only primary searchparameters 108, e.g. 108, 108 b, such as within a search string 106, mayoften yield a large found set 138 of results 134, e.g. 134 a-134 j. Insome embodiments of the enhanced search system 10, such as integratedwith a conventional search engine 12, an enhancement of a search 24 maycomprise processing 22, e.g. refinement 22 a and/or organization 22 b,of a found set 138 from a search 24. The enhanced source solicitationcontrol 126, 128 shown in the primary search result screen 132 allows auser USR to operate 22 on the results of a search 24, such as bynavigation to a enhanced search system source selection screen 120, asseen in FIG. 10.

The source solicitation screen 132 may alternately comprise a selectionsources 16 which are implicitly determined, such as based on enteredsearch parameters 108. For example, in a user USR entered search string106 which includes a term lodging, a choice of travel specific sources16 may be provided for the user USR, such as to refine a search basedupon ratings from one or more travel-related sources 16.

The search enhancement system 10 is readily implemented to provide agreat value for a user USR, in which information from one or moresecondary sources 16 can be explicitly or implicitly accessed andintegrated to refine or organize the results of a search. The searchenhancement system 10 improves current search methodologies, since auser USR can specify one or more user-selected information sources to beconsulted by a search application module 46 when performing a search.Results 14 from a conventional search engine 12 may be refined orre-organized based on data independently maintained by a selected source16, such as a ratings service 16.

In either case, the results obtained using a conventional search may becompared against the identified source ratings service 16 and filtered22 a and/or sorted 22 b appropriately. System functions may be performedby an integrated search engine 44, or alternatively, by an applicationmodule 44 associated with a search engine 12, such that no modificationis necessary to the conventional search engine 12.

Since conventional search engines 12 allow only explicit entry of searchterms 106, 108, such as within a search string interface 104, a user USRis typically required to repeat searches using a plurality ofcombinations of search parameters 108 and search strings 106, in orderto receive an acceptable quality and quantity of search results, i.e.hits.

The enhanced search system 10 provides structures and associatedprocesses which allow a user USR to enhance either the search or theresults of a search, based upon information from one or more selectedsources. A wide variety of selectable sources 16, from whichsupplementary information 18 is accessed, may be used, such as externalservices 16, e.g. ratings services, or user-specified sources, e.g. suchas user-defined ratings or search parameters.

Enhanced Search System having Personal Search Parameters. Some preferredembodiments of the enhanced search system 10, such as 10 g (FIG. 15),comprise the selection 33 of one or more user-specified searchparameters 148, e.g. 148 a (FIG. 12).

Some embodiments of the enhanced search system 10 having personal searchparameters 148 comprise a solicitation of general search parameters 148from a user USR, before a particularized search 24 is initiated 52. Thesolicited search parameters 148 are thereafter associated with the userUSR, such that parameters 148 are available for automatic integrationinto future particularized searches initiated 52 by the user USR.

FIG. 12 is a schematic diagram 140 which shows user specification 146a-146 p of one or more secondary search parameters 148 a-148 p, such asthrough a user interface 142. The specified parameters 148 a-148 p aretypically stored 150, such as at one or more locations, which can belocated at a wide variety of locations within an enhanced search system10, such as within a user terminal 32, at an enhanced search applicationmodule 46, in combination with a search engine 12, or at one or morelocations throughout the system, such as at a service provider or apersonal web site.

The generalized search parameters 148 may pertain to a variety ofdifferent subject matters 168 (FIG. 13), and represent informationuseful in enhancing a search for a user USR and/or other recipients RCP,such as by filtering, further filtering, or sorting search resultsobtained when performing searches 54. For example, generalized searchparameters 148 may include the user's address and health insurancecarrier, such that future particularized searches for medical careproviders may be automatically refined or organized based on proximityand eligibility.

In a conventional search environment, a user USR must often enterdetailed personal search parameters within a search string, if personalcriteria are to be considered at the time of a search. Therefore, a userUSR is often required to understand the search engine, and to rememberthe parameters at the time of the search.

The use of user specified generalized search parameters 148 readilyprovides an improved search environment, since a user USR is notrequired to manually manipulate a conventional search engine 12, throughthe entry of detailed search parameters 108, to consider personalcriteria at the time of a particularized search. As well, a user USR isnot required to understand the detailed string parameter format 106 of asearch engine 12, nor is a user USR required to remember and enterpersonalized parameters 148 at the time of a search.

The use of generalized search parameters 148 relieves the user USR ofthe burden of sifting through pages of search results that are notrelevant or customized to their needs, for instance, medical careproviders the are not proximate to their home or eligible under theirinsurance in the example above.

FIG. 13 is a schematic diagram 160 of an user-specified search parameter148 and subject validities, i.e. rankings 170. A search parameter 148typically comprises a parameter value 166 entered by a user USR, such aswithin a parameter value entry window 164 within a user interface 142(FIG. 12).

A search parameter 148 may also preferably comprise an entered ordetermined ranking 170 for one or more subjects 168, e.g. 168 a-168 s,such that an applicability or validity of the parameter 148 can beexplicitly or implicitly determined, i.e. such as in a determination ofinclusion within a an enhanced search 24, or within search resultrefinement 22 a and or sorting 22 b. The search parameter 148 shown inFIG. 13 comprises applicability rankings 170, e.g. 170 a-170 t for atleast one subject matter 168. An exemplary quantized ranking 170 may beranked as Yes or No, one or more divisions between 0% to 100%, a numericvalue of 1 to 5, or another rating value scale 170. A ranking 170 ispreferably associated with each of the generalized search parameters 148for a particular subject matter 168, so that results satisfying severalof the criteria may be appropriately sorted.

Based upon the determined subject matter 168 of a search query 13, auser specified parameter 148 having a rankings 170 which is determinedto be applicable to the search may either be used in conjunction withprimary search terms, i.e. to further limit search results, or may beused to sort the results of a query based upon primary search criteria,wherein the sort is based upon the applicability ranking 170 of one ormore generalized search parameters 148.

FIG. 14 is a detailed schematic diagram 172 of an exemplary enhancedsearch parameter 148, having a parameter value 166 of “95103” for a homeaddress zip code, along with subject validities, i.e. rankings 170 for aplurality of subjects 168, such as local services 168 a, online shopping168 b, and health care 168 s. As seen in FIG. 14, a ranking 170 t of 100percent applicability is associated with local services 168 a, such thata search for a local service may preferably include the home addressparameter 166 of the user USR.

To enable automatic association of appropriate parameters with futureparticularized searches, generalized user-specified search terms arepreferably stored or associated with a label or type. In the exampleabove, for instance, search terms may be stored as follows:

-   Health Insurance Carrier: Kaiser-   User's Home Address: Street Address City, State, Zip-   User's Work Address: Street Address City, State, Zip

Thereafter, at the time of a particularized search by the user USR, thesubject matter of the search 24 is identified or through explicit entryby the user USR, the relevant types of generalized search parameters 148are identified based on the subject matter 124 of the search 24. Againusing the example above, if the system 10 determines that a user USRseeks to search for a medical care provider, the generalized searchparameters 148 of location and medical insurance provider may preferablybe identified as relevant to this particularized search 24. Whereavailable, user-specified information 18 related to those parameters areextracted from the general search parameters 148 associated with theuser USR. Parameters 148 that are determined to be relevant can be usedin any of a variety of ways, such as to return 22 a or organize 22 bbetter search results, or to perform a search 24 using the availablesubset of optimal parameters 148.

In some system embodiments, the system 10 solicits the user USR toprovide any missing parameters at the time of the particularized search.For example, if the user-specified parameters do not include theinsurance carrier of a user USR, a exemplary search for a medical careprovider may be performed by supplementing the user's input withlocation alone, or the user USR may be asked for their medical insuranceprovider at the time of the particularized search.

FIG. 15 is a functional block diagram of an enhanced search system 10 gcomprising personal search parameters 148. FIG. 16 is a flowchartshowing an exemplary process 200 for an enhanced search system 10 g,comprising personal search parameters 148, and the refinement 22 ofsearch results 14 based upon one or more personal search parameters 148which are determined to be relevant to the search.

As seen in FIG. 15, a user USR interacts 71 with an application module46, typically between a user interface 142 at a user terminal 32 and theapplication module 46. Typical interactions 71 between a user terminal32 and the application module 46 comprise input and definition 182 ofparameters 148, search initiation 52, the return of standard, i.e.non-enhanced, search results 73, parameter prompts 184, sourceidentification inputs 33, and/or the return 41 a,41 b of enhancedresults 40.

Some embodiments of the enhanced search system 10, such as the enhancedsearch system 10 g shown in FIG. 15, preferably provide user selectededitorial searches, e.g. such as editorially ranked content, i.e.editorial commentary, corresponding to user input, which can then bereturned 40 a to the user USR, or sent 40 b to recipients RCP, such asto send to selected peer recipients RCP of the user USR. In some systemembodiments, the recipients RCP comprise one or members of a network ofpeople associated with a user USR, e.g. such as node recipients RCP in anetwork of people with similar interests, or a chain of friends, e.g.such as established through the Internet, e.g. friendster.com.

The enhanced search system 10 g shown in FIG. 15 may alternately provideenhanced results 40 which are filtered in part, i.e. refined 22 a and/ororganized 22 b, based upon information 18 received from an externalsource 16, such as from the most popular people and/or places in theuser's personal network.

The enhanced search system 10 g and an associated method 200 thereforeprovide an enhancement to a search system, in which general searchparameters are solicited from a user USR, either before or after aparticularized search, such as through button selection within a userinterface 142. In some system embodiments, the solicited searchparameters are preferably associated with user selectable editorialcontent, such as for delivery to the user USR and/or to other recipientsRCP, and are available for automatic integration into futureparticularized searches, such as initiated by the user USR or by otherrecipients RCP that are associated with the user USR, such as a networkof friends, family, peers, students, neighbors, people or entities witha zip code region, and/or business associates.

In the exemplary process 200 shown in FIG. 16, a user USR is preferablyable to initially store 202 user-specified search parameters 148. When auser USR initiates a search query process 52, an identification of thesubject matter may also be identified 204, such as through explicitentry, e.g. through subject selection 125 (FIG. 10), or through animplicit determination 206 at the application module 46, e.g. based uponthe entered search parameters 108 and parameter string 106. If thesubject matter of the query is not 210 determined, the applicationmodule 46 solicits 212 and receives 214 the subject matter from the userUSR. If the subject matter of the query is 216 determined, the system 10selects 212 one or more user-specified search parameters 148 based onthe subject matter, either for refinement 22 a, sorting 22 b of searchresults 14, or for integration 210 of the selected user-specified searchparameters 148 with a query 13.

Upon receipt 33 of source identification from a user USR, theapplication module 46 typically sends a data query 36 to any identifiedsources 16, if the available data 18 from an identified source 16 is notyet available. Upon a data query 36, the data 18 is sent from anidentified source 16, either to be included in a search query 13, or tobe used in the processing 22 of search results 14. The applicationmodule 46 produces 22 the enhanced results 40, which are then sent 41,such as by returning 41 a the enhanced results 40 to the user terminal32, and/or by sending 41 b the enhanced results 40 to one or morerecipients RCP.

The enhanced search system 10 g seen in FIG. 15 provides storage of aset of user-specified search parameters, and automatically integratesselected ones of the stored search parameters into a search query 13,based on the subject matter of that query 13. The subject matter of thequery may be explicitly indicated by the user USR, or may beinferentially determined, based on user input.

In some embodiments of the enhanced search system 10 g, general searchparameters are typically solicited 184 from a user USR before aparticularized search 13 is initiated. The solicited search parameters148 are associated with the user USR, whereby the parameters 148 areavailable for automatic integration into future particularized searchesinitiated by the user USR.

The storage 150 of personal parameters may be located at a wide varietyof locations within the system 10 g, such as within a file stored on theuser's computer 132 (FIG. 6). The general search parameters 148 may alsobe associated with a user's roaming profile, passport, or init packet,such that the system 10 g may readily access personal parameters 148 foran identified user USR.

The determination and maintenance of generalized search parameters 148can be provided by a wide variety of entities, such as but not limitedto the application module 46, an independent enhancement module thatworks in conjunction with a conventional search engine 12 or as anapplication, utility, or application plug-in within a user terminal 32.

The enhanced system 10 g is readily adapted to a wide variety of networkstructures, such as within an integrated search engine structure 44(FIG. 6), or within an application module 46 which is retrofit to anexisting, i.e. conventional, search engine 12. As well, the appropriatesubject matter of a particularized search can be identified either atthe application module 46, or even at a user terminal 32, e.g. such asfor local storage or parameters 148 and refinement 22 a and/or sorting22 b of search results 14.

In some system embodiments 10 g, the user-specified search parametersare integrated into a search string and are therefore used to producethe number of resulting hits. In alternate embodiments of the enhancedsearch system 10 g, user-specified parameters 148 are applied to theresults of a search that is performed without their integration, such aswithin a system 10 g which is retrofit to an existing search engine 12.

In some enhanced search system embodiments 10, at the time of aparticularized search, an interface is presented to the user USR, whichallows a customized search query, and enables the user USR to modifyout-dated or unwanted search parameters.

Conventional search engines 12 typically operate in an objective manner,based upon search parameters 108 within a parameter string 106 input atthe time of a search. As well, the search results of a conventionalsearch engine are often sorted as a function of commercial or popularparameters.

The enhanced search system 10 g and personal search parameters 148 allowthe results of a search engine 12 to be enhanced 22, such as throughrefinement 22 a and/or sorting 22 b, to reflect the desired or intendedfocus of the user USR. Furthermore, the determined subject matter of thesearch allows the enhanced results 40 to reflect more subjective resultsthan are provided in an objective search engine alone.

Although the enhanced search system and methods of use are describedherein in connection with a user terminal, the apparatus and techniquescan be implemented for a wide variety of electronic devices and systems,such as personal computers, mobile devices, and othermicroprocessor-based devices, such as portable digital assistants ornetwork enabled cell phones, or any combination thereof, as desired. Aswell, while the enhanced search system and methods of use are describedherein in connection with interaction between a user terminal and anapplication module and search engine across a network such as theInternet, the enhanced search system and methods of use can beimplemented for a wide variety of electronic devices and networks or anycombination thereof, as desired.

Accordingly, although the invention has been described in detail withreference to a particular preferred embodiment, persons possessingordinary skill in the art to which this invention pertains willappreciate that various modifications and enhancements may be madewithout departing from the spirit and scope of the claims that follow.

1. A method implemented across a network, comprising the steps of:transmitting to a user an interface for explicitly entering at least onequantized relevance value by the user in association with at least onegeneral search parameter in regard to at least one subject matter, theinterface comprising at least one general parameter value entry windowfor entering a general search parameter and at least one entry field forentering a quantized relevance value by the user to be associated withan entered general search parameter; receiving through the interface ageneral search parameter entered by the user, and a quantized relevancevalue entered by the user in association with a subject matter categoryand the entered general search parameter; associating the receivedentered quantized relevance value and the received entered generalsearch parameter with the user; and storing the associated quantizedentered relevance value and the associated entered general searchparameter at a location that is accessible across the network.
 2. Themethod of claim 1, wherein the associated quantized relevance value andthe associated entered general search parameter are stored at any of auser terminal, a search application module, a service provider, and apersonal web site.
 3. The method of claim 1, wherein the associatedquantized relevance value and the associated entered general searchparameter are stored at one or more locations throughout the network. 4.The method of claim 1, wherein the quantized relevance values compriseany of an applicability and a validity of at least one of the enteredgeneral search parameters in regard to at least one subject matter. 5.The method of claim 1, wherein the at least one entry field for enteringa quantized relevance value is selectable to comprise any of yes or no,one or more divisions between 0% and 100%, a numeric value of 1 to 5,and a rating value scale.
 6. The method of claim 1, further comprisingthe steps of: receiving a query initiated by the user; accessing theassociated quantized relevance value and the associated general searchparameter from the storage location across the network; determining ifthe associated entered general search parameter is relevant to the queryinitiated by the user, based on the quantized relevance value; andintegrating the accessed the accessed general search parameter the queryinitiated by the user to perform a search, based on the relevancedetermination.
 7. The method of claim 1, further comprising the stepsof: receiving a search query from the user over the network; retrievingthe stored associated entered quantized relevance value and theassociated entered general search parameter; categorizing the receivedsearch query within the subject matter category; determining therelevance of the associated entered general search parameter within thecategorized subject matter category, based on the associated enteredquantized relevance value; and enhancing a search using the associatedentered general search parameter if the associated entered generalsearch parameter is determined to be relevant to the categorized subjectmatter category, wherein the enhancement comprises any of using thegeneral search parameter in conjunction with the received search queryto perform the search if the general search parameter is determined tobe relevant; performing the search with the received search query andsubsequently refining search results with the general search parameterif the general search parameter is determined to be relevant; andperforming the search with the received query and subsequently providingany of organizing and sorting of the search results with the generalsearch parameter if the general search parameter is determined to berelevant.
 8. The method of claim 1, further comprising the steps of:receiving a search query from the user over the network; retrieving thestored associated quantized relevance value and the associated enteredgeneral search parameter; categorizing the received search query withinthe subject matter category; and determining the relevance of theassociated entered general search parameter within the subject mattercategory, based on the quantized relevance value; in response to thesteps of categorizing the search query and determining the relevance,creating a set of search parameters based on the search query, theassociated entered quantized relevance value and the associated enteredgeneral search parameter; and performing the search based on the set ofcreated search parameters, wherein the step of performing the searchbased on the set of created search parameters comprises any of: usingthe general search parameter in conjunction with the received searchquery to perform the search if the general search parameter isdetermined to be relevant; performing the search with the receivedsearch query and subsequently refining search results with the generalsearch parameter if the general search parameter is determined to berelevant; and performing the search with the received query andsubsequently providing any of organizing and sorting of the searchresults with the general search parameter if the general searchparameter is determined to be relevant.
 9. The method of claim 8,further comprising the step of: sending the results of the refinedsearch to the user.
 10. The method of claim 8, further comprising thestep of: sending the results of the refined search to a recipient otherthan the user.
 11. The method of claim 10, wherein the recipient is anyof selected by the user and determined based on any of the results ofthe refined search and information input by users.
 12. The method ofclaim 10, wherein the recipient is any of a selected peer, a friend, afamily relative, a student, a neighbor, any of a person or entity withina zip code region, and a member of a network of people associated insome manner with the user.
 13. The method of claim 1, further comprisingthe steps of: receiving information from a recipient other than theuser; and selectively sending results of the refined search to therecipient based upon any of the received information from the recipientand a selection of the recipient by the user.
 14. The method of claim13, wherein the received information comprises any of a characteristicof the recipient and an interest in the results of the refined search bythe recipient.
 15. The method of claim 1, wherein the step ofdetermining the subject matter of the received search query comprisesany of explicit indication by the user and inferential determinationbased upon user input or action.
 16. The method of claim 1, furthercomprising the steps of: obtaining from the user at least one parameterafter receipt of the query at the time of the search.
 17. The method ofclaim 1, further comprising the steps of: receiving at least one sourceselection from the user; and modifying the search query based uponinformation from the selected source.
 18. The method of claim 1, whereinthe step of obtaining the general search parameters from the user occursany of before and after a particularized search.
 19. The method of claim1, wherein the entered general search parameter comprises any of theuser's address and the user's health insurance carrier.
 20. The methodof claim 1, wherein user inputs through the interface are any ofsolicited and explicitly entered.
 21. A system implemented across anetwork, comprising: an interface for explicitly entering at least onequantized relevance value by the user in association with at least onegeneral search parameter entered by the user in regard to at least onesubject matter, the interface comprising at least one general parametervalue entry window for entering a general search parameter by the userand at least one entry field for entering a quantized relevance value bythe user to be associated with an entered general search parameter;means for receiving through the interface a general search parameterentered by the user, and a quantized relevance value entered by the userin association with a subject matter category and the entered generalsearch parameter; means for associating the received entered quantizedrelevance value and the received entered general search parameter withthe user; and means for storing the associated quantized enteredrelevance value and the associated entered general search parameter at alocation that is accessible across the network.
 22. The system of claim21, wherein the associated quantized relevance value and the associatedentered general search parameter are stored at any of a user terminal, asearch application module, a service provider, and a personal web site.23. The system of claim 21, wherein the associated quantized relevancevalue and the associated entered general search parameter are stored atone or more locations throughout the network.
 24. The system of claim21, wherein the quantized relevance values comprise any of anapplicability and a validity of at least one of the obtained generalsearch parameters in regard to at least one subject matter.
 25. Thesystem of claim 21, wherein the at least one entry field for entering aquantized relevance value is selectable to comprise any of yes or no,one or more divisions between 0% and 100%, a numeric value of 1 to 5,and a rating value scale.
 26. The system of claim 21, furthercomprising: means for receiving a query initiated by the user; means foraccessing the associated quantized relevance value and the associatedgeneral search parameter from the storage location across the network;means for determining if the associated entered general search parameteris relevant to the query initiated by the user, based on the quantizedrelevance value; and means for integrating the accessed the accessedgeneral search parameter the query initiated by the user to perform asearch, based on the relevance determination.
 27. The system of claim21, further comprising: means for receiving a search query from the userover the network; means for retrieving the stored associated enteredquantized relevance value and the associated entered general searchparameter; means for categorizing the received search query within thesubject matter category; means for determining the relevance of theassociated entered general search parameter within the categorizedsubject matter category, based on the associated entered quantizedrelevance value; and means for enhancing a search using the associatedentered general search parameter if the associated entered generalsearch parameter is determined to be relevant to the categorized subjectmatter category, wherein the enhancement comprises any of means forusing the general search parameter in conjunction with the receivedsearch query to perform the search if the general search parameter isdetermined to be relevant; means for performing the search with thereceived search query and subsequently refining search results with thegeneral search parameter if the general search parameter is determinedto be relevant; and means for performing the search with the receivedquery and subsequently providing any of organizing and sorting of thesearch results with the general search parameter if the general searchparameter is determined to be relevant.
 28. The system of claim 21,further comprising: means for receiving a search query from the userover the network; means for retrieving the stored associated quantizedrelevance value and the associated entered general search parameter;means for categorizing the received search query within the subjectmatter category; and means for determining the relevance of theassociated entered general search parameter within the subject mattercategory, based on the quantized relevance value; means for creating aset of search parameters based on the search query, the associatedentered quantized relevance value and the associated entered generalsearch parameter, in response to a categorization the search query and adetermination of the relevance of the associated entered general searchparameter within the subject matter category; and means for performingthe search based on the set of created search parameters, wherein thestep of performing the search based on the set of created searchparameters comprises any of: means for using the general searchparameter in conjunction with the received search query to perform thesearch if the general search parameter is determined to be relevant;means for performing the search with the received search query andsubsequently refining search results with the general search parameterif the general search parameter is determined to be relevant; and meansfor performing the search with the received query and subsequentlyproviding any of organizing and sorting of the search results with thegeneral search parameter if the general search parameter is determinedto be relevant.
 29. The system of claim 28, further comprising: atransmission of the results of the refined search to the user.
 30. Thesystem of claim 28, further comprising: a transmission of the results ofthe refined search to a recipient other than the user.